code: def test_dkwm_mean_two_sample_assertion_beta_1_2_false(self, dtype):
      rng = np.random.RandomState(seed=0)
      num_samples = 4000
      samples1 = rng.uniform(size=num_samples).astype(dtype=dtype)
  
      # As established above, 4000 samples is enough to find discrepancies
      # of size 0.2 or more with assurance 1e-6.
  
      # Test that the test assertion confirms that the mean of the
      # standard uniform distribution is different from the mean of beta(1, 2).
      beta_low_samples = rng.beta(1, 2, size=num_samples).astype(
          dtype=dtype
      )
      with self.assertRaisesOpError("true mean greater than expected"):
          self.evaluate(
              st.assert_true_mean_equal_by_dkwm_two_sample(
                  samples1,
                  0.0,
                  1.0,
                  beta_low_samples,
                  0.0,
                  1.0,
                  false_fail_rate=1e-6,
              )
          )
  
imports: import functools
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 18 for calling the StatisticalTestingTest obj's underlying member method code with example usage: obj.test_dkwm_mean_two_sample_assertion_beta_1_2_false(dtype) without return types